25 citations · 43 across the 6 of their papers we have counts for
8 papers
BenCSSmark: Making the Social Sciences Count in LLM Research
Arnault Chatelain, Étienne Ollion, Qianwen Guan +7
This position paper argues that the under-representation of social science tasks in contemporary LLM benchmarks limits advances in both LLM evaluation and social scientific inquiry…
Automatic Classification of News Subjects in Broadcast News: Application to a Gender Bias Representation Analysis
Valentin Pelloin, Lena Dodson, Émile Chapuis +2
This paper introduces a computational framework designed to delineate gender distribution biases in topics covered by French TV and radio news. We transcribe a dataset of 11.7k hou…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Improving Multimodal fusion via Mutual Dependency Maximisation
Pierre Colombo, Emile Chapuis, Matthieu Labeau +1
Multimodal sentiment analysis is a trending area of research, and the multimodal fusion is one of its most active topic. Acknowledging humans communicate through a variety of chann…
Code-switched inspired losses for generic spoken dialog representations
Emile Chapuis, Pierre Colombo, Matthieu Labeau +1
Spoken dialog systems need to be able to handle both multiple languages and multilinguality inside a conversation (\textit{e.g} in case of code-switching). In this work, we introdu…
Hierarchical Pre-training for Sequence Labelling in Spoken Dialog
Emile Chapuis, Pierre Colombo, Matteo Manica +2
Sequence labelling tasks like Dialog Act and Emotion/Sentiment identification are a key component of spoken dialog systems. In this work, we propose a new approach to learn generic…